collaborators

5 papers

q-fin.RM2024

Analysis of an aggregate loss model in a Markov renewal regime

Pepa Ramírez-Cobo, Emilio Carrizosa, Rosa Elvira Lillo

In this article we consider an aggregate loss model with dependent losses. The losses occurrence process is governed by a two-state Markovian arrival process (MAP2), a Markov renew…

stat.ML2024

Variable selection for Naïve Bayes classification

Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez-Cobo +1

The Naïve Bayes has proven to be a tractable and efficient method for classification in multivariate analysis. However, features are usually correlated, a fact that violates the N…

stat.ME2024

A cost-sensitive constrained Lasso

Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez-Cobo +1

The Lasso has become a benchmark data analysis procedure, and numerous variants have been proposed in the literature. Although the Lasso formulations are stated so that overall pre…

stat.ME2024

A bivariate two-state Markov modulated Poisson process for failure modelling

Yoel G. Yera, Rosa E. Lillo, Bo F. Nielsen +2

Motivated by a real failure dataset in a two-dimensional context, this paper presents an extension of the Markov modulated Poisson process (MMPP) to two dimensions. The one-dimensi…

stat.CO2024

Fitting procedure for the two-state Batch Markov modulated Poisson process

Yoel G. Yera, Rosa E. Lillo, Pepa Ramírez-Cobo

The Batch Markov Modulated Poisson Process (BMMPP) is a subclass of the versatile Batch Markovian Arrival process (BMAP) which has been proposed for the modeling of dependent event…